Abstract
In multiple target tracking the data association, observation to track fusion, is crucial and plays an important role for success of any tracking algorithm. The observation may be due to true target or may be clutter. In this paper, data association problem is viewed as an optimization problem and two methods, (i) using neural network and (ii) using the evolutionary algorithm, have been proposed and compared. © Springer-Verlag Berlin Heidelberg 2004.
Cite
CITATION STYLE
Zaveri, M. A., Merchant, S. N., & Desai, U. B. (2004). Data association for multiple target tracking: An optimization approach. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3316, 187–192. https://doi.org/10.1007/978-3-540-30499-9_27
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
